The present invention relates to the field of precision farming. More particularly, this invention relates to an application of precision farming to measure and map crop quality.
The concept of providing the best resources to the most efficient users of the resources has been around for a long time. This concept is also present in agriculture. One of the most common applications of this concept is to a herd of dairy cattle. Dairymen weigh the milk from each cow and tailor the feed ration to match the productive potential of the particular cow. For example, the most productive cows may have gotten an extra scoop of grain in the old days. Nowadays, the concept has been further refined so that the production from a particular cow is optimized with several inputs.
The concept has been extended in the agricultural setting to crops and the fields which produce the crops. Individual areas of cropped fields have different production potentials. Existing technology now allows yield maps to be constructed for cropped fields. Over the course of several years, farmers can monitor the yields as well as the resources devoted to producing the yields. Once a base amount of data is obtained for a particular individual area of a field, the farmer can then alter some of the resources applied to an individual area and note the effects in terms of the yield. Ultimately, the farmer can optimize the resources used to produce an optimized yield. This will allow farmers to reduce the use of chemicals, irrigation water and other inputs to cropped fields to a bare minimum. The farmer is able to maximize profit by minimizing the expenses necessary to produce a crop. The environment is also favorably impacted since only a minimum amount of chemicals is applied to the field.
The concept of optimizing the inputs to individual areas of a field has been called precision farming. Practical application of precision farming has grown rapidly with the introduction of relatively inexpensive global-positioning systems. One might say that the less expensive global-positioning systems have enabled precision farming to emerge from a textbook concept to something that can be applied today by farmers. Tractors are outfitted with a computer having memory, and a global-positioning system so that the individual areas of the fields can be located. The locations of the individual field areas and their respective treatment are stored in the computer. The global-positioning system identifies the particular field areas. The computer retrieves the information with respect to the inputs or the resources to be applied to the particular area of the field and then controls various implements to apply the resources appropriately. For example, a planter is controlled by a computer during planting to dispense more or less seed to the land in a specific individual area of the field. Another implement controlled by a computer in an application of precision farming is an applicator used to distribute fertilizer, herbicides or other chemicals to the field at spatially-variable rates. The digital map containing the rate at which the applicator applies each of these chemicals to each area of the field is stored in the onboard computer which is connected to the global-positioning system.
The current applications of precision farming in use today have some deficiencies. Amongst the deficiencies is the overemphasis of yield as the only meaningful output. There is a need to expand to other meaningful outputs so that application of resources to crops can be optimized with regard to these other outputs. There is also a need to factor all the meaningful outputs or measures into decisions for application of resources. In addition, there is a need for tracking other outputs and for tracking crops with respect to other outputs for future applications of precision farming.
In this invention, precision farming is given the capability to measure and map the quality of the product from a field crop or an orchard crop. For field crops a harvester equipped with a global-positioning system is enhanced by the addition of a system to mark samples for quality analyses as well as measure the quantity of the harvested product.
The farmer selects a sampling pattern for mapping quality parameters. Values representing longitude and latitude for the selected sampling points are loaded into storage on a computer or are recorded. The harvester includes a dispenser of crop markers. Each crop marker has a unique identifier, when compared to the other crop markers used to harvest a large area, that can, ideally, be remotely scanned. The global-positioning system determines actual field location during the harvest, and when an actual field location is close to or matches one of the selected field sample locations, a trigger signal is sent to the dispenser and a crop marker is inserted into the harvested crop stream. As the marker is deployed or inserted into the crop stream, the marker""s unique identifier number is scanned, and recorded in a table of field sample locations versus crop marker identification numbers. Later on in processing, the crop marker is detected and a sample of the crop is taken from the volume surrounding the crop marker. A quality test is performed on the sample, and a map for each quality parameter is constructed using the table of positions at which each marker was inserted into the stream of harvested crop.
A similar system is used for orchard crops, except in this case the new system includes both recording the yield and maintaining the identity of quality samples from each tree. This system uses the same remotely scannable identification tags and scanners specified for the field crop harvester. The system is tailored to meet the needs of a hand-picked crop. It accomplishes the following: (1) records the weight of crop picked by each employee, (2) records the weight of crop produced by each tree, and (3) maintains the tree identity of a sample of fruit from each tree upon which quality analyses can be performed.
Each tree is marked with a permanent ID, such as with numbers on the field, row, and tree number within each row. Plastic cards with electronically scannable tags are attached to each tree. The scannable tags may directly read out the information used for the permanent ID. The scannable tag may also read out an identifier other than the information used to permanently mark the tree. If the identifier is different than the permanent ID information, then a table is needed to correlate the identifier with the permanent ID.
A second set of plastic cards are also prepared for each employee picking fruit. The cards can also be of any size but preferably are about the size of playing cards. Each card is also imprinted with the employee number of each picker. Prior to harvest, a table of the employee number versus identification tag number is prepared by keying in the imprinted numbers and scanning the identification number on each tag.
Each picker wears two markers or scannable tags, one to identify the tree and one to identify the picker. The picker fills a sample bag with a portion of fruit. Two scanners are used to scan the marker tags. The picker walks across a scale to the fruit storage unit. The weight of the picker is subtracted from the combined weight of the picker and the fruit each time the picker crosses the scale. The weight of fruit from the tree can then be totaled. A marker from the tree is also used or attached to a bag containing a representative sample from the tree. Quality tests are run on the fruit in the sample bag.